Systems and methods related to dynamically orchestrating execution of a protocol by generating one or more executors and one or more functions using a network controller based on the protocol are disclosed. In one example embodiment, there is provided a method of receiving a user-defined logic to allow the network controller to generate a dataset including a plurality of accumulators, abstract one or more executors and functions, and generate a set of protocols at the one or more functions to activate a respective application stage to fulfill the service request based on the logic in near real-time. Moreover, methods herein may include determining a telemetry and/or insight generation based, at least in part, on the dataset.
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5. They system of claim 1, wherein each of the plurality of accumulators comprises shared variables accessible by the respective application stages.
The invention relates to a distributed computing system designed to improve data processing efficiency in multi-stage applications. The system addresses the challenge of managing shared data between different processing stages in a distributed environment, where traditional methods often suffer from bottlenecks, synchronization delays, or inconsistent data access. The system includes multiple accumulators, each associated with a specific application stage. These accumulators store shared variables that are accessible by the respective stages, allowing seamless data exchange without requiring direct inter-stage communication. Each accumulator is configured to collect and aggregate data from its associated stage, ensuring that the shared variables reflect the latest processing state. The accumulators may also include mechanisms to handle concurrent access, such as locking or versioning, to prevent data corruption while maintaining high throughput. The system further includes a coordination mechanism that manages the flow of data between accumulators, ensuring that updates propagate correctly across stages. This coordination may involve scheduling, conflict resolution, or consistency checks to maintain system reliability. The accumulators may be implemented as in-memory data structures, disk-based storage, or a hybrid approach, depending on performance and persistence requirements. By using shared variables within accumulators, the system reduces the overhead of inter-stage communication, minimizes synchronization delays, and improves overall processing efficiency. This approach is particularly useful in large-scale distributed applications where multiple stages must collaborate to process data in a coordinated manner.
6. The system of claim 1, wherein each of the plurality of accumulators comprises labeled and unlabeled object instances based on metadata.
This invention relates to a data processing system that categorizes and manages object instances using accumulators, which are data structures that store both labeled and unlabeled object instances. The system addresses the challenge of efficiently organizing and retrieving objects in large datasets where some objects have associated metadata labels while others do not. The accumulators dynamically group objects based on their metadata, allowing for flexible querying and analysis. Each accumulator contains a mix of labeled and unlabeled instances, enabling the system to handle incomplete or partially annotated datasets. The system may further include mechanisms to update or refine the labels over time, improving the accuracy of object classification. The accumulators can be used in applications such as machine learning, data mining, or information retrieval, where distinguishing between labeled and unlabeled data is critical for training models or extracting insights. The invention ensures that objects are processed and stored in a way that preserves their metadata context, facilitating more effective data management and analysis.
10. The system of claim 1, wherein the plurality of application stages comprises an intent detection, analytics, computation, experimentation, prediction, and action stage.
This invention relates to a system for processing and analyzing data through a structured sequence of application stages. The system addresses the challenge of efficiently handling complex data workflows by breaking them into distinct, specialized stages to improve accuracy, scalability, and automation. The system includes multiple interconnected stages, each designed to perform a specific function in the data processing pipeline. These stages include intent detection, which identifies the purpose or goal of the input data; analytics, which extracts meaningful insights from the data; computation, which performs necessary calculations or transformations; experimentation, which tests hypotheses or models; prediction, which forecasts future outcomes based on the processed data; and action, which executes decisions or actions based on the predictions. The system is designed to streamline data workflows by ensuring each stage is optimized for its specific task, reducing errors and improving overall efficiency. The modular structure allows for flexibility, enabling customization and integration with other systems as needed. This approach enhances the system's ability to handle diverse data types and complex analytical tasks while maintaining high performance and reliability.
16. The method of claim 13, wherein each respective application stage receives the respective set of second protocols and executes an action based on the respective set of second protocols and the first dataset.
This invention relates to a system for dynamically managing application workflows through protocol-based execution. The technology addresses the challenge of efficiently processing data across multiple application stages, where each stage must adapt its operations based on evolving protocols and input datasets. The system involves a workflow manager that distributes a first dataset to multiple application stages, each configured to perform specific tasks. Each stage receives a set of second protocols, which define the actions to be taken on the first dataset. The protocols may include rules, parameters, or instructions that dictate how the data should be processed, transformed, or analyzed. The application stages execute their respective actions based on the received protocols and the first dataset, ensuring consistent and coordinated processing across the workflow. This approach allows for flexible and scalable data handling, where protocols can be updated or modified without requiring changes to the underlying application logic. The system is particularly useful in environments where workflows must adapt to changing requirements or data conditions, such as in real-time analytics, automated decision-making, or distributed computing systems.
17. The method of claim 13, wherein the network controller fulfills the request for service in near real time (NRT).
A system and method for network service provisioning involves a network controller that dynamically allocates resources to fulfill service requests. The network controller monitors network conditions, including available bandwidth, latency, and device capabilities, to determine optimal resource allocation. When a service request is received, the network controller evaluates the request against current network conditions and user preferences to select the most suitable resources. The system prioritizes requests based on urgency, service type, and user priority levels, ensuring efficient resource utilization. In some implementations, the network controller fulfills service requests in near real time (NRT), minimizing delays and improving responsiveness. The system may also include mechanisms for load balancing, quality of service (QoS) management, and dynamic reallocation of resources to adapt to changing network conditions. The method ensures reliable and efficient service delivery while optimizing network performance.
20. The computer program product of claim 18, wherein the plurality of application stages comprises an intent detection, analytics, computation, experimentation, prediction, and action stage.
This invention relates to a computer program product for managing and optimizing application workflows, particularly in systems requiring dynamic decision-making and adaptive responses. The technology addresses the challenge of efficiently processing complex, multi-stage workflows where different stages must interact seamlessly to achieve desired outcomes. The program product includes a plurality of application stages that collectively handle various aspects of workflow execution. These stages include intent detection, which identifies the purpose or goal of the workflow; analytics, which processes and interprets data to extract meaningful insights; computation, which performs necessary calculations or transformations; experimentation, which tests different approaches or configurations; prediction, which forecasts future outcomes based on historical or real-time data; and action, which executes the final decisions or adjustments. Each stage is designed to operate in a coordinated manner, allowing the system to adapt to changing conditions, optimize performance, and achieve objectives efficiently. The invention improves upon existing systems by providing a structured yet flexible framework for managing complex workflows, ensuring that each stage contributes to the overall goal while maintaining scalability and adaptability.
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October 26, 2022
May 14, 2024
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